News
EU projects collaborate for Trustworthy AI Across Europe
Horizon Europe supports nine initiatives to boost solid and trustworthy AI across Europe Nine projects funded under Horizon Europe call HORIZON-CL4-2021-HUMAN-01-01 will pave the way for the widespread acceptance of Artificial Intelligence (AI) across Europe....
Press Release: Introducing SAFEXPLAIN: Trustworthy AI through Deep Learning solutions that meet European Safety Standards for Industry
Barcelona, 18 October 2023—The newly released video from the EU-funded SAFEXPLAIN project explains how it tackles safety and explainability challenges associated with the use of deep learning (DL) solutions in critical autonomous systems, like cars, trains and satellites.
Four Ways of Testing how to Minimize Risk of Injury in Automatic Train Operation
Partner Ikerlan is pursuing the development of two safety functions that will minimize the risk associated with Automatic Train Operation. Two scenarios offer approaches for minimizing the risk of a train running over or injuring people on the track as well as avoiding damages during opening/closing operations on the platform. Four activities are underway to support these scenarios.
Taking Automatic Train Operation further: implementing safety functions to minimize risk
The challenge faced by the railway case study is closing the gap between Functional Safety Requirements and the nature of Deep Learning (DL) solutions. Functional Safety systems need deterministic, verifiable and pass/fail test-based software solutions.
SAFEXPLAIN talks Safety and AI at the 2023 VDA Conference on Quality, Safety and Security for automotive Software-based Systems
VDA pocket programme cover SAFEXPLAIN partner EXIDA development presented the SAFEXPLAIN project and the platform framework overview during the first day of the VDA Automotive SYS conference focusing on Quality, Safety and Security for Automotive Software-based...
Gauging requirements and testing models for Space, Automotive and Railway Case Studies
Using three case studies from different industrial domains ensures that the project considers the needs of multiple fields whose common thread is the potential use of autonomous systems in complex environments, where AI can enable critical and powerful features.
COMPSAC 23: Presenting acceleration solutions based on Deep Neural Networks (DNNs) for use in safety-critical systems
BSC researcher Martí Caro presented “Efficient Diverse Redundant DNNs for Autonomous Driving” on 27 June 2023 at the Autonomous Systems Symposium (ASYS) within the 47th IEEE International Conference on Computers, Software & Applications (COMPSAC). The theme of...
Talking about Automotive Functional Safety at Automotive SPIN Italia
Safexplain project partner EXIDA-dev presented at the 21st Workshop on Automotive Software and Systems hosted by Automotive SPIN Italia
Integrating Explainable AI techniques into Machine Learning Life Cycles
Written by Robert Lowe & Thanh Bui, Humanized Autonomy Unit, RISE, Sweden. Machine Learning life cycles for data science projects that deal with safety critical outcomes require assurances of expected outputs at each stage of the life cycle for them to be...
SAFEXPLAIN to present in COMPSAC Autonomous Systems Symposium
The paper "Efficient Diverse Redundant DNNs for Autonomous Driving", coauthored by BSC authors Martí Caro, Jordi Fornt and Jaume Abella, has been accepted for publication in the 47th IEEE International Conference on Computers, Software & Applications (COMPSAC)....